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import unittest
from numpy import array
import Orange.classification.naive_bayes as nb
from Orange import preprocess
from Orange.data.sql.table import SqlTable
from Orange.data import Domain
from Orange.data.variable import DiscreteVariable
from Orange.tests.sql.base import DataBaseTest as dbt
class NaiveBayesTest(unittest.TestCase, dbt):
def setUpDB(self):
self.conn, self.iris = self.create_iris_sql_table()
def tearDownDB(self):
self.drop_iris_sql_table()
@dbt.run_on(["postgres"])
def test_NaiveBayes(self):
iris_v = ['Iris-setosa', 'Iris-virginica', 'Iris-versicolor']
table = SqlTable(self.conn, self.iris,
type_hints=Domain([],
DiscreteVariable("iris",
values=iris_v)))
disc = preprocess.Discretize()
table = disc(table)
bayes = nb.NaiveBayesLearner()
clf = bayes(table)
# Single instance prediction
self.assertEqual(clf(table[0]), table[0].get_class())
# Table prediction
pred = clf(table)
actual = array([ins.get_class() for ins in table])
ca = pred == actual
ca = ca.sum() / len(ca)
self.assertGreater(ca, 0.95)
self.assertLess(ca, 1.)
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